JPH06168223A - Pipe network analyzing device, data display device for the same and graphic generating method - Google Patents

Abstract

PURPOSE:To provide the pipe network analyzing device capable of calculating the result of analyzing a detailed pipe network at high speed. CONSTITUTION:Hierarchical pipe network data 1 provided with coarse pipe network data 11 and detailed pipe network data 12 concerning an objective area and demand data 2 are prepared, the analysis of the coarse pipe network is executed by a gloval pipe network analysis part 7 corresponding to these pipe network data 1 and demand data 2, the detailed pipe network data corresponding to a small block designated by an MMI/F 3 for designating the small block of the pipe network inside the objective area are selected from the detailed pipe network data 12 of the pipe network data 1 by a pipe network data selection part 5, these selected detailed pipe network data are worked by a gloval result work part 6 while using the analyzed result of the gloval pipe network analysis part 7, and pipe network calculation concerning yhe detailed pipe network is executed by these worked detailed pipe network data and the demand data 2 concerning the detailed pipe network selected by a demand data selection part 4.

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a pipe network analysis device used for pipe network analysis of waterworks and the like and a data display device thereof.

[0002]

2. Description of the Related Art Recently, due to speeding up of computer processing, the flow rate and head value of water in a water supply network are calculated based on the demand amount of water, and the water supply system for simulating these trends is calculated. Pipe network analysis calculation has been put to practical use.

Such a network analysis is carried out by a water supply network.
If the size of the network becomes large, the amount of calculation becomes considerably large, and further, when it is necessary to calculate this pipe network analysis calculation in a short time such as interactive control or real-time display, further speedup is required.

By the way, it is desirable that such a network analysis be conducted over the entire target area where the pipeline network is closed, but especially in urban areas, such an area is very large and the network The size also increases. Therefore, in the case of calculation over such a wide area, the network is contracted and changed to a coarse network to analyze the network.

However, according to the conventional pipe network analysis, even when it is desired to know the detailed analysis result in some areas,
Since the network analysis is performed for the entire system with the closed network, detailed network calculations had to be performed for the entire target area.

For this reason, for example, when it is desired to quickly know the detailed analysis result of a small network in some small areas, the conventional method can be used to calculate the detailed network. Although an analysis result with a pipe network is obtained, it takes too much calculation time.On the other hand, if a coarse pipe network is used for analysis, high-speed calculation is possible, but the result itself is for a coarse pipe network. As a result, there is a problem that detailed analysis results cannot be obtained in a short time.

Conventionally, as a data display device for displaying the result data of such a pipe network analysis, there is one that appropriately switches between a display for a coarse pipe network and a display for a detailed pipe network. However, these displays are simply switched and displayed, and at present, there is no one that can effectively switch the viewpoints and the display methods together with the switching of these displays. In addition, at present, there is no one that effectively displays the results of pipe network analysis at the same time as displaying the map of the target area.

[0008]

As described above, in the related art, when it is desired to quickly know the local analysis result in a detailed network, the calculation with the detailed network takes too much time, while High-speed calculation is possible if analysis is performed with a coarse network, but since this result is for a coarse network, there was a drawback that detailed network results could not be obtained in a short time. It is possible to effectively switch the view point and display method associated with the switching of the display of the results for the pipeline network and the detailed results for the pipeline network, and also to display the pipeline network analysis results together with the graphic display of the target area. Is currently not found.

The present invention has been made in view of the above circumstances, and an object of the present invention is to provide a pipe network analysis apparatus capable of calculating a local analysis result for a detailed pipe network at high speed. It is another object of the present invention to provide a data display device capable of effectively displaying display data together with a graphic display of a map of a target area.

[0010]

Means for Solving the Problems The present invention provides a means for preparing hierarchical network data and demand data having coarse network data and detailed network data for a target area, and the hierarchical network data and demand. Means for performing an analysis on a coarse network by means of data; means for designating a small area of the network within the target area; and detailed network data corresponding to the small area designated by this means for the hierarchical management. Means to select from detailed network data of network data and demand data for detailed network
Means for selecting data, means for processing the detailed network data selected corresponding to the small area according to the analysis result for the rough network, demand data for the detailed network and the processed data. It is configured by means for executing a pipe network calculation for the detailed pipe network based on the detailed pipe network data.

The present invention further includes means for storing graphic data and attribute data, means for registering a display method for the graphic data and attribute data stored in this means, and the stored graphic data and attribute data. On the other hand, it comprises a display target area and a means for selecting a display target, and means for searching the display target area selected by this means for a display method most suitable for the display target and performing data display.

On the other hand, a third aspect of the present invention is based on each of the data of an external figure composed of an outer contour line and data of at least one inner figure composed of an inner contour line included in the outer figure. A first step of extracting the contour line of a figure, and a second step of structuring the shape information of each of the outer figure and the inner figure and the inclusion relation between each figure based on each of the extracted contour lines. Based on the step and the structured shape information and inclusion relation, the inner figure and the outer figure, or the inner figure and another inner figure included in the same outer figure including the inner figure are connected. And a fourth step of generating one closed figure by connecting the outlines of the figures using the pseudo-connection line. Characterize.

[0013]

As a result, according to the present invention, the hierarchical network information and the demand information in the target area are given, the network analysis for the coarse network is executed, and the network analysis result in the coarse network is used to perform the small scale analysis. Detailed pipe network data corresponding to the area is processed, and the processed detailed pipe network data and the demand data for the detailed pipe network are processed.
It is designed to execute the network calculation for the detailed network. This makes it possible to calculate the detailed analysis results of the pipe network at a high speed when a part of the target area is specified, and to display the local analysis of the pipe network. You will get a quick response.

Further, according to the present invention, these display methods are registered for the graphic data and the attribute data, and when the display target area and the display target are selected for the graphic data and the attribute data, the selection is made. The optimum display method for the display target is searched for in the display target area and the data is displayed. As a result, it becomes possible to effectively display the display data as well as the graphic display of the map of the target area by setting the appropriate viewpoint.

On the other hand, according to the third aspect of the invention, the contour lines of the outer figure and the inner figure are extracted from the data of the figure consisting of one outer figure and at least one inner figure, and based on each extracted contour line. , Shape information of each outer and inner figure,
The inclusion relation between each figure is structured, and based on the obtained shape information and the inclusion relation, a pseudo connecting line for connecting each of the inner figure, the outer figure, and the inner figure is generated, and this pseudo connecting line is generated. Is used to connect the contour lines of each figure to generate one closed figure. This makes it possible to handle a perforated figure consisting of an outer figure and an inner figure as one figure.
Therefore, for example, in computer graphics, there is an advantage that a patch for filling can be generated only by considering only the unevenness of the contour shape of the generated figure.

[0016]

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS First, the formulation of a water supply network analysis, which is a concrete example of the network calculation handled in the present invention, will be described. In this case, the networks that make up the network are represented by a graph structure consisting of nodes. Here, the pipe network analysis is to calculate the head of water (sum of water pressure and altitude) at each node and the flow rate at each arc. The data necessary for the calculation of the pipe network are the pipe network data, the water distribution site data, and the water demand data.

Here, for the network data, the graph structure of geometric information and the attribute information of nodes and arcs are used. No
The attribute of the code is a classification of supply point and consumption point. A supply point is a water distribution site and represents a point of supplying water, and a consumption point represents a point of consuming water. A parameter (R) corresponding to resistance is an attribute of the arc. This parameter is the following Hazen-Williams equation, which is often used in pipe network analysis, between the flow rate of the arc (Q) and the head loss (H) which is the difference between the heads of the nodes at both ends. Used for.

H = R · Q ^1.85 (1) Hereinafter, this parameter R is referred to as resistance. That is, the pipe network data has this resistance value as an arc attribute. By using this relation, the flow rate and head loss can be calculated mutually.

Water demand data is water consumption data for each region.
It is This data is known to the water supply company (local government). If this data is not given, it can be approximately calculated using the demand and the total floor area for each building application. Water demand data for pipe network analysis
All the consumption nodes of pipe network data shall be assigned the consumption of water. Moreover, the water distribution site data is the data of the water head value at the water distribution site corresponding to the supply node.

Thus, the equations basically established in the pipe network model are that the difference between the inflow and outflow in each node is equal to the demand amount in that node, and that the Hazen-Williams equation for the head loss is There are only two types. Pipe network analysis is a calculation method for obtaining the head and flow rate that satisfy these relational expressions.

(First Embodiment) FIG. 1 shows a schematic construction of a pipe network analyzing apparatus in consideration of this fact. In this case, the pipe network data 1 and the demand data 2 are prepared in advance. Further, the pipe network data 1 in the embodiment is made up of two types, that is, coarse pipe network data 11 and detailed pipe network data 12 in the target area. Here, all of the coarse tube network
A detailed network node is associated with each node, and has a hierarchical data structure. This is a common technique for efficiently managing large-scale network structures. Demand data 2 is water consumption data for each region.

Then, the MMI / F (man-machine interface)
Face) 3, demand data selection unit 4, pipe network data selection unit 5, global result processing unit 6, global pipe network analysis unit 7, local pipe network analysis unit 8, display unit 9 It is composed by.

With such a configuration, if a small area which is now a part of the target area is designated by MMI / F3, the detailed network data 12 of the network data 1 is used to create a small area in that area. The pipe network analysis result of is calculated.

In this case, the demand data selecting section 4 generates the demand data 2 relating to the detailed pipe network. Further, the pipe network data selecting section 5 selects a local pipe network in this small area from the detailed pipe network data 12. The global result processing unit 6 selects the local information of the small area designated by the MMI / F3 from the global result calculated by the global pipe network analysis unit 7. Then, the local pipe network analysis unit 8 uses this local information to perform the pipe network calculation in the local detailed pipe network, and displays the result on the display unit 9.

In this case, in this embodiment, the simulation is performed in real time interactively by changing the demand data 2 and the network data 1 in the designated area in the MMI / F3. You can do it.

Further, the embodiment will be described in detail.
The hierarchical network data which is the data 1 is as shown in FIG. In the figure, the nodes of the coarse network are 1, 2, 3, 4
Of the four nodes numbered, the first node is, for example, a water distribution plant. These four nodes are common nodes. Also, as an arc, 1
-2 (ark connecting node 1 and node 2), 1-3, 2
There are four, -3 and 3-4. On the other hand, the detailed network nodes are numbered 1, 2, 3, 4, 5, 6, 7, 8 and the arcs are 1-2, 1-3, 2 -3, 2-5,
3-5, 3-6, 4-6, 4-7, 7-8. In this case, only the three arcs 1-2, 1-3, and 2-3 are common to the coarse pipe network.

FIGS. 3 and 4 show an example of each node data and arc data of the detailed pipe network shown in FIG. 2, and FIGS. Node data and aer of coarse pipe network shown
An example of data is shown.

The coordinate values of the node data shown in FIGS. 3 and 4 represent coordinates on the map coordinate plane. Also, in the supply column, which is the attribute of each node, write 1 and its head value at the supply point of the water distribution plant, etc.
Is described. Also, in the column of the corresponding node of the coarse network of the node data of the detailed network shown in FIG. 3 and the corresponding node of the detailed network of the node of the coarse network shown in FIG. In the column, enter the node number only when there is a corresponding (coordinate value is equal) node in the coarse (detailed) node data and there is no corresponding point. Indicates 0. In addition, each arc data shown in FIGS. 4 and 6 describes the node number and the resistance value of the starting point and the ending point thereof. Furthermore, FIG.
Is an example of the demand data 2, and each coordinate value (x
_i , y _i ) (i = 1, 2, ..., I),
It indicates that each has its own demand.

With respect to such network data 1, the global network analysis unit 7 shown in FIG. 1 allocates the demand data 2 to each node of the coarse network. Start to calculate. In this case, the heads at all nodes of the rough network provided as shown in Fig. 5 and the flow rates at all arcs given as shown in Fig. 6 were calculated to obtain global results. Like This calculation can be performed at high speed because the amount of data is small.

Then, the small area which is a part of the target area is designated by the MMI / F3, and the designation is made to designate the area indicated by the frame A as shown in FIG. As a result, using the global results obtained by the global pipe network analysis unit 7, the demand data selection unit 4, the pipe network data selection unit 5, the global result processing unit 6, and the The local network analysis unit 8 obtains a detailed local analysis result in the network as described above.

In this case, the pipe network data selection unit 5 uses the MMI.
Extract the local detail network and boundary detail network within the frame specified by / F3. The local detailed network here is a network that collects the arcs from both the detailed network and both ends of the arc within the specified frame. The boundary detailed network is the network. Only one of the two is a set of arcs that enter the frame, and the nodes that enter the frame are called internal nodes.

The generation of these two types of network data can be judged for the detailed arcs of the entire network by using the coordinate values of the endpoints thereof. Next, the demand data selection unit 4 allocates demand amounts to all the consumption nodes of the local detailed pipeline network data. In the case of demand data as shown in FIG. 7, since the coordinate value of each demand point is known, the node that is closest to that demand point (calculated from the coordinate value) is consumed for each demand point. Can be assigned. And each consumption of the pipe network
It is calculated by taking the sum of the demand demands assigned to each.

On the other hand, in the global result processing section 6,
The heads at all nodes in the Kal detail network are calculated as follows. In this case, the head values of all nodes of the detailed network are approximated in advance by the values of the coarse network. For example, each coefficient of the equation in the case of first-order approximation is determined in advance by the least-squares method with respect to the head value of the network calculation result for various demand data in the detailed network. This linear interpolation formula allows the water head value of each node of the detailed pipe network to be determined.

Then, the local pipe network analysis unit 8 uses the data generated by the global result processing unit 6 to determine all the flow rate and head of the local detailed pipe network. Here, as a simple method, the head value determined in the global result processing section 6 is used to determine all the flow rates from the relational expressions (such as the Hazen-Williams equation) between the head loss and the flow rate. . Furthermore, by using the hydraulic head determined by the global result processing unit 6 or the flow rate determined here as an initial value, the pipeline network analysis program can be executed to perform analysis in the local detailed pipeline network. .

The local result output from the local network analysis unit 8 is displayed on the display unit 9. Therefore, in this way, when a part of the target area is specified, it is possible to calculate the detailed analysis results of the pipe network at high speed, and display the local analysis of the pipe network. You will get a quick response.

(Second Embodiment) Next, a data display device for displaying the results of the pipe network analysis thus obtained as simulation data will be described.

FIG. 9 shows a schematic structure of such a data display device. In this case, 21 is a CPU, and a database (DB) 22, a knowledge base (KB) 23, and a CRT 24 are connected to this CPU 21. Then, when the data of the DB 22 is designated by the MMI / F 25, the display method is searched from the KB 23 described later by referring to the data category from the data, and the network analysis is performed on the CRT 24 according to the display method. It is designed to display the results. Here, the CPU 21 controls the entire apparatus. Further, the DB 22 is shown in FIGS.
As shown in (c), the town block boundary graphic data and the administrative boundary graphic DB having the block graphic data, the house graphic DB, and the network DB having the node data and the arc data are associated with each other. In addition to the above, it also has the above-mentioned simulation data water flow and hydraulic pressure data as network attribute data.

However, in such a configuration, as shown in FIG.
As shown in FIG. 1, first, DB2 in the MMI / F25
The second administrative boundary figure DB is selected (step 111), and then the display target area and the display target category are selected (step 112). Then, the water flow and hydraulic pressure data, which are the simulation data, are read from the administrative boundary graphic DB as the attribute data of the network together with the town pattern data or the block graphic data of the display area. Then, the viewpoint setting method of the category selected from the KB 23 is searched by these data (step 113), the optimum viewpoint coordinates for data display are obtained (step 114), and the viewpoint setting is performed (step 115). The data is displayed (step 116).

In this case, the KB 23 sets the categories for the administrative boundary figure, the house figure, and the simulation data used for the display in advance, as shown in FIG. 12, and also registers the viewpoint setting method for these categories. is doing. For example, when displaying water pressure node data, it is displayed together with the map, but in order to understand the map, the map should be oriented northward upward, and water pressure node data should be viewed diagonally from above. Registers various viewpoint setting methods. In addition, in the case of water pressure surface data display and water flow display, a viewpoint setting method for looking down the target area of the map from directly above is registered. Then, when displaying data, the viewpoint coordinates are obtained using these registered setting methods, and the system automatically sets the viewpoint based on the viewpoint coordinates.

It should be noted that the KB 23 registers the display method such as the balance of the display of the display object, the maximum area of the display object on the screen, and the maximum number of faces constituting the display object. You can also Although these viewpoint setting methods are registered in the KB 23 in principle, the user may give specific candidates for the viewpoint coordinates in order to reduce the processing. In this case, the system automatically performs the process of obtaining the optimum viewpoint coordinates from the viewpoint coordinates of the candidate, but since the viewpoint coordinate candidates are based on the method registered in KB23, the range is limited. The candidate coordinates will be given in.

Next, as a method of obtaining the viewpoint coordinates, a method of determining a specific numerical value of the viewpoint will be described. In the case of two-dimensional display, the position is set so as to look down from directly above the center of the display target area.

On the other hand, in the case of three-dimensional display, the viewpoint setting example [1] (2) shown in FIG. 12 will be described. First, in order to determine the position of the viewpoint when displaying the designated area, As shown in FIG. 13, the viewpoint 132 is set at a distance from the center of the map display target area 131 so that all the cylinders indicating the water pressure of the nodes in that area are displayed. In this case, since the map is generally viewed with the north facing upward, images of several points of view height as shown in FIGS. 14A to 14C are generated and occupied by the cylinders. Find the position of the viewpoint that maximizes the number of pixels.
Here, in the method of counting the number of pixels, the number of pixels in the filled portion shown in FIG. 15 is counted.

Here, if the object is the same and the map area has the same size, the same viewpoint coordinates are automatically set for the reference point (center of the map area). 16A and 16B, the position of the viewpoint requested by the user can be determined by rotating the display object around the reference point 161 of the display object as shown in FIGS. When displaying multiple categories of data, if the displayed objects have the same priority, the viewpoint for the simulation data is given priority. In the case of simulation data of a plurality of categories, the viewpoint coordinates are determined by a weighted average considering the priorities of the viewpoints.

Next, a display example based on the viewpoint coordinates thus determined will be described. In this case, the case of water pressure and water flow as the data to be selected will be described. First, when displaying the simulation data as it is on the node, the water pressure display will be from KB23 shown in FIG. ]
Areas related to (1) and (2)) and their nodes are selected and displayed as shown in FIG. 17 (a).
The display ([1] (3), (4)) is selected, and the display shown in FIG. 17 (b) is performed. In addition, when displaying the water flow on the network in the display area, the water flow is displayed from KB23 shown in FIG. 12 (KB [2]
(1) and (2)) are selected, and the display shown in FIG. 17C is performed. Further, in the case of displaying the numerical information of the flow velocity in the water flow display, ([2] (1)) is selected from KB23 shown in FIG. 12, and as shown in FIG.
Numerical values will be displayed near the arc.

In the case of re-display, if the size and the display category of the display target area are the same, the process of obtaining the optimum viewpoint coordinates is not performed, and the viewpoint having the same positional relationship with the center of the display target area is not performed. The coordinates are automatically set and the display is started.

Further, as shown in FIG. 19 (a), the water flow data display shown in FIG. 20 (b) with the viewpoint directly above the display target area and the display as shown in FIG. 20 (a). In the case of simultaneously displaying objects of different categories to be displayed, such as the water pressure data display shown in FIG. 21B in which the viewpoint is tilted at a predetermined angle with respect to the target area, FIG. As shown, the viewpoint may be set for the display target area and the display as shown in FIG.

Therefore, in this way, by registering the display method for the display target in the KB, it is possible to effectively display the display data together with the graphic display of the map of the target area by setting the appropriate viewpoint. .

(Third Embodiment) By the way, as a three-dimensional image processing method for surface display, cross-section display, and content display for a three-dimensional display, 1.3-dimensional data has been used as a voxel data. Raster display as a data, 2. It is known to generate shape figures from the contours extracted from slice images, treat these shape figures as a polyhedron, and perform surface display and cross-section display.The former method is to extract the contents. When displaying, a special device is required to perform high-speed extraction, and the latter regenerates a new shape figure between the cross section and the shape figure, and determines the cutting relationship between the shape figures. It is necessary to re-execute, and the amount of processing for calculating the cutting state of the cross section depends on the number of geometric figures, and a large amount of calculation is required, which is an obstacle to high-speed display.

Therefore, in the third embodiment, 3 from the original image.
It is possible to easily display the surface of a three-dimensional object, its cross section, and the contents. FIG. 22
Shows a schematic configuration of the third embodiment. In the figure,
The CPU 31 reads the original slice image from the DISK 32, performs preprocessing, performs processing such as viewpoint setting, display color, and display detail specified by the MMI / F 33, and displays the result on the CRT 34. .
Further, when a cross section is designated by the MMI / F 33, preprocessing for displaying the cross section is performed, and the result is displayed on the CRT 34.

In this case, as shown in FIG. 23, first, an arbitrary slice image is input from the disc (step 2).
31). Then, for this slice image, a rendition in which the coordinates of the start point and the end point of the run are obtained from a binary image with an arbitrary threshold value is generated (step 232), and labeling, inclusion relation, The contour line information chain code and the closed figure extraction for obtaining the contour vector are extracted (step 233). This is performed for each slice to generate three-dimensional data, and then the viewpoint is determined and shading is displayed (step 234). A cross section is designated for the display (step 235), and a cross section is generated (step 236). Then, when the cross-section is displayed, the cut-off closed figure for which the labeling, the inclusion relation, the contour line information chain code, and the contour vector are obtained is extracted using the cross-section-related land data (step 237). Three-dimensional data for cross-section display is generated and displayed.

In this case, the closed figure extracted in step 233 in FIG. 23 is labeled with labels 241-243 as shown in FIGS. 24 (a) and 24 (b) and is a closed figure formed from the outer contour line 244. A closed figure formed from the outer figure 245 and the inner contour line 246 is called an inner figure 247. Also, outside figure 2
A plurality of inner figures 247 included in 45 are sibling figures 2
48, and the inner figure 247 included in the outer figure 245 has a parent-child relationship.

The three-dimensional data generated by using the data labeled in step 234 of FIG. 23 is generated as shown in FIGS. 25 (a) to 25 (d). In this case, in order to generate three-dimensional data, as shown in FIG.
When the contour line 261 is obtained as shown in (a) and the vertex coordinates of the closed figure are obtained based on the contour chain code (see FIG. 2).
6 (b)) and a case where the vertex coordinates of the closed figure are obtained from the contour vector (FIG. 26 (c)). Here, in the former case, it is treated as high-definition display primitive data, and in the latter case, it is treated as object outline display primitive data. If the outer figure 245 and the inner figure 247 have a parent-child relationship, the inner figures 247 are connected by a pseudo connecting line 271 as shown in FIG.
As shown in (b), a part of the inner figure 247 is connected to the outer figure 245 by the pseudo connecting line 272 to generate three-dimensional data as one primitive. Further, as shown in FIG. 28, the sibling figure 248 is replaced with the pseudo connecting line 281.
In order to connect with each other, the pseudo connecting lines 282 are obtained in the order of the shortest distance between the vectors of the inner figures 245, and the pseudo connecting lines 282 among those candidates that do not interfere with other sibling figures are connected to the pseudo connecting lines 281. To decide.

Then, the three-dimensional data obtained in this way
Although the data is projected and displayed, in this case, since it is modeled as a shape figure that is faithful to the density value of the input image, the color added to the shape data is the same as when the slice image was input. A color corresponding to the density value can be assigned.

With respect to this display, the cross section is designated in step 235 in FIG. 23 and the cross section is generated in step 236. When the target object is cut here, the cross section is created based on the land data. Primitive data for display
Generate data.

The processing procedure for generating the primitive data for displaying the cross section is shown in steps 291-296 of FIG.
In this case, since the cutting line on the plane including each slice is obtained from the cutting plane, the start point and the end point of the cutting line are obtained for the slice where the cutting line exists, and the processing for obtaining the cutting point is performed.

First, from the equation of the plane representing the cutting plane, the cutting line in the plane including the slices is shown in FIG.
It is determined as shown in (a). A cutting point sequence 305 for cutting the run is obtained from the starting point 302 and the ending point 303 of the cutting line included in each slice representing the cutting surface 301. As shown in FIG. 32 (a), the cutting point here is a point on the cutting line that is first generated in a new scan line when a point sequence of cutting lines is obtained in numerical order in the y direction.
Here, 321 indicates a cutting point, 322 indicates a cutting line, and numbers indicate the order in which the point sequence of the cutting line 322 is generated.

Specifically, steps 311 to 311 in FIG.
The breakpoint is determined using the procedure of 17. The method for obtaining this break point is the integer Bresenham algorithm (Brese
nham, J .; E, “Algorithm for Computer Putter Control
of a Digital Plotter ”, IBM System Journal
al, Vol. 4, pp. 25-30, (1965)), which is an improvement of the straight line generation method. Here, the integer Bresenham algorithm increments x and y according to the slope of the straight line, and introduces an approximated error with a sign when examining the error between the position of the actual straight line and the closest point, The point forming the straight line is determined by taking only the sign into consideration. Δ in FIG. 31 represents the approximated error. Δx and Δy represent absolute values of the difference between x and y at the starting point and the ending point of the cutting line. In the function sing (n), the sign of the value of n is minus,
When it is zero and plus, -1, 0 and 1 are returned, respectively.
The function Interchg (n1, n2) swaps the values of n1 and n2. The chg flag has 1 or 0 depending on the magnitude relationship between Δx and Δy. The cutting point in this embodiment is set to be the first point generated in a new scan line when scanning in the raster direction in the point sequence generated by the above algorithm. As shown in FIG. 31, by introducing the flag Plot_flg, the integer type Brese
In the point sequence generated by the nham algorithm, Plot
A point only when the value of _flg is 0 is set as a cutting point.

Next, returning to FIG. 30B, the run 304 to be cut is extracted. The run data cut in each slice is uniquely determined from the start point and end point coordinates of each run and the cutting point sequence 305. A closed figure including the cut random data is extracted, and a rectangular area including the closed figure is obtained. In the coordinate system shown in FIG. 30B, when the cutting line is y = const (constant), a closed figure including the land data whose scan line number is const is extracted, and a rectangular area including the closed figure is extracted. Will be asked.

Then, in step 237 of FIG. 23, the closed figure is extracted for the rectangular area containing the cut closed figure. In this case, FIG. 33A to FIG.
As shown in (c), the closed figure composed of the disconnected land data and its parent-child relationship are regenerated.

In the figure, the closed figure 332 is regenerated and a new label is attached, with the upper left part of the cutting point sequence 331 as the display part. In the cut closed figure extraction process, the closed figure extraction, parent-child relationship between the closed figures, and sibling relationship can be determined by only scanning once the rectangular area including the cut closed figure. Also, since the 3D data before cutting is stored, if there is a closed figure that is not cut and is included in the rectangle, the 3D primitive generated from the modified closed figure is included. Display with data.

In this embodiment, it is possible to display the contents of the target object having different density values by arbitrarily setting the threshold value for generating the binary image and extracting the closed figure. . Further, it is possible to display the contents by semi-transparent display by using a display device or a display system capable of semi-transparent display. Further, when the cross-section is displayed, the contents can be displayed, and it is possible to easily take out and display only the contents having an arbitrary density value in the input slice image.

Therefore, by doing so, it becomes possible to efficiently perform surface display, cross-section display, and content display of a three-dimensional object from the original slice image group without requiring a special device.

(Fourth Embodiment) Next, a fourth embodiment of the present invention will be described. In addition, the outside figure in the following description,
The inner figure and contour lines (outer contour line and inner contour line) are the same as those defined in the third embodiment with reference to FIG.

By the way, in the third embodiment, in the three-dimensional image processing system for displaying the surface, the cross-section, and the contents of the three-dimensional display, the original slice image group can be obtained without requiring a special device. From the above, the three-dimensional graphic processing method capable of efficiently displaying the surface, the cross-section, and the contents of the three-dimensional object has been described. Among them, based on the run data of the perforated figure as shown in FIG.
As shown in FIG. 7, a process of connecting the outer figure and the inner figure or the inner figures with each other by a pseudo connecting line to generate three-dimensional data was performed.

Hereinafter, in the fourth embodiment, a plurality of closed 1
For the perforated figure consisting of one outer contour line and one or more inner contour lines (that is, outer figure and inner figure), the above-mentioned process of connecting the outer figure and the inner figure or the inner figures with a pseudo connecting line A description will be given of a method for generating a figure in which the original perforated figure is represented by a single closed contour line by connecting the contour lines of the respective figures using the pseudo connection line as an actual connection line.

By the way, in the area extraction method in the conventional computer graphics filling processing of perforated figures, the correspondence between the outer figures and the inner figures or the vertices of the inner figures is found, and the vertices are connected to form a patch. A general method is to generate a basic figure for so-called filling and perform the filling process.
In this method, when determining the correspondence between the outer figure and the inner figure, or the vertices of the inner figures, in order to avoid the destruction of the shape of other inner figures, the sequence of candidates for the correspondence between those vertices is generated. However, there is a drawback that it requires a trial and error process of sequentially determining corresponding vertices and that the processing time is long. Further, when the closed figure is subjected to a process for reducing the number of vertices in order to simplify the geometrical shape as shown in FIG. 26C, line segments that should not be connected should intersect with each other. There is a case in which a closed figure has a twist, but when filling such a closed figure, it is not possible to adopt a computer graphics filling algorithm that considers only the irregularities of the contour shape of the figure, and twist is detected. , It was necessary to adopt a fill algorithm that added processing that would not hinder the fill.

Therefore, in the fourth embodiment, it is possible to regenerate the outer figure and the inner figure as one figure for the perforated figure without the trial and error processing required in the conventional processing method. I have to. In addition, when regenerating in such a way, by locally removing the twisted portion in the closed figure and adding the process of correcting the geometric shape,
It is possible to adopt a patch generation method for filling computer graphics that considers only the irregularities of the contour shape of the generated figure, and to perform shape regeneration excluding a plurality of internal figures.

That is, in the graphic generation method of this embodiment,
As shown in FIG. 34, an outer figure composed of outer contour lines,
And a step of extracting the contour line of each figure from the data of the figure which is included in the outer figure and is composed of at least one inner figure composed of the inner contour line, and each of the outer figure and the inner figure. (402) for structuring the shape information of, and the inclusion relationship between each figure,
(403) generating a pseudo connecting line for connecting the inner figure and the outer figure, or the inner figure and another inner figure included in the same outer figure that includes the inner figure and the outer figure; The method is characterized in that it includes a step (404) of generating one closed figure by connecting the outlines of the figures using connecting lines.

As will be described later, when connecting the outer figure and the inner figure by connecting lines to generate one figure, interference between line segments in the closed figure, that is, a twisted portion is detected, and twisting occurs. For the two line segments, the points between the line segments are adopted to divide the line segments, and the process of detecting the interference for the newly generated line segment is locally repeated to obtain the figure shape. I made a correction to.

Hereinafter, the fourth embodiment will be described more specifically. FIG. 35 shows a schematic configuration of the fourth embodiment. This apparatus is a scanner 40 that optically measures the shape of a three-dimensional structure for each layer having a certain interval and takes in gradation image data as a continuous tomographic image.
The gradation image data input from the scanner 40 is converted into a binary image, the contour lines of the figures are traced and labeled, the list of inclusion relations between the figures is generated, and the figures having the inclusion relation are regenerated. A processor 41 that performs three-dimensional modeling based on these figures, and a storage device 4 that stores the geometric information obtained by this processor 41.
2 and a display device 44 for drawing the geometric information stored in the storage device 42.

FIG. 36 shows details of the graphic generation processing by the processor 41. First, the image data stored in the storage device 42 is input (step 400),
The contour line extraction (step 401) is performed from this image data, the labeling of each figure and the inclusion relationship between the figures (that is, the relationship between the outer figure and the inner figure) are obtained, and these data are included in the inclusion relationship list as shown in FIG. It is registered in 411 (step 402). Note that the contour line extraction process may be performed using a known one, for example, refer to the document [Junichiro Toriwaki, Digital Image Processing 2 for Image Understanding, Shokoido, pp. 66
-78].

Next, pseudo connecting lines are generated in a uniform direction from each inner figure, and the figure labels and line segment numbers of the inner figure or outer figure having the first intersection of the pseudo connecting lines are as shown in FIG. Registered in the automatic connection information table 412 (step 4)
03).

Next, pre-processing for single connection of outer and inner figures is performed. That is, paying attention to the end point of the pseudo connecting line, that is, the line segment of the outer figure / inner figure, and referring to the table created in advance, the inner figure label that generated the pseudo connecting line is connected as shown in FIG. Register in the table 413. After the connection line table is generated, the connection of the outline of the graphic is started from one vertex of the external graphic, and the closed graphic is regenerated via the outline of the internal graphic via the pseudo connection line (step 40).
4).

Three-dimensional modeling is performed on the basis of the regenerated closed figure (step 405), and display is performed on the display device 44 (step 406). Hereinafter, such a processing procedure will be described in more detail.

The processor 41 extracts the contour line according to the method described in the above document. The contour line tracking here is a pixel tracking type. Simultaneously with the tracing of the contour line, labeling of the inner and outer figures is performed to generate a list of inclusion relations between the inner figure and the outer figure. Then, in the inclusion relation list 411 shown in FIG.
A pointer for the parent figure number and a pointer for the child figure number are stored. For example, when the target graphic includes the outer graphic 441 and the inner graphic 442 and 443 as shown in FIG. 38, the label number of the list of the outer graphic 441 in the inclusion relation list of FIG. 37 is "L1". , "NILL" for the outer figure number pointer p11, link data to the list of one inner figure 442 for the inner figure number pointer p12, and the other inner figure 4 for the inner figure number pointer p13.
The link data to the list of 43 is written respectively. Further, the label number of the list of the internal figure 442 is "L.
2 ", the outer figure number pointer p21 has link data to the list of the outer figure 441, the inner figure number pointer p22 has" NILL ", and the inner figure number pointer p23 has link data to the list of the other inner figure 442. 37. The list of the other inner figure 442 is omitted in FIG.

On the other hand, although the chain code of the figure is obtained as a result of the contour line extraction, the number of vertices of the figure can be reduced based on the chain code. For example, the literature [Rammer, U .; E. , "An interat
Ive procedure for the poly
generalization ”, Compu
ter Graphics and Image Pr
Processing, Vol. 1, pp. 244-256
(1972)]. In addition, there are various other methods, and any of them can be applied to this embodiment.

The figures that can be generated by these methods are
It is a line-segment-approximated figure having a contour line with a smaller number of vertices than the figure formed by the chain code, and twisting may occur in the figure as shown in FIG. FIG. 4 showing a part of a group of vertices forming a figure
In FIG. 0 (a), each square represents a pixel, and the dotted line represents a case where pixels are faithfully connected to the chain codes of the line segments m and n. Further, the solid line represents a line segment that constitutes a figure approximated by the line segment, and is twisted as shown in the figure. The vertex sequence of the figure considering the chain code only for the line segments m and n is P1 → P2 → P3 → P4 → P5 → P6.
→ P7 → P8 → P9 → P10 → P11 → P12 → P13
Is. The vertices P1 and P6, and the vertices P3 and P
10 is the same pixel. The vertex sequence of the same figure in the line segment approximation is P1 → P2 → P3 → P7 → P8 → P12 → P1
It is 3.

In this embodiment, the twist shown in FIG. 39 is removed by applying the processing shown in FIG. 39 to all the line segments. First, with respect to all the line segments in the figure, it is checked whether or not the line segment that should not be originally connected to the line segment has an intersection at a point other than the end points of the line segment (step 421). If there is an intersection, a point corresponding to the middle point of the chain code group existing between the start point and the end point of each of the two line segments is adopted as a new vertex of the figure (step 422). . The vertex P5 in FIG. 40 (b) and the vertex P10 in FIG. 40 (c) are the midpoints of the chain code groups of the line segments m and n, respectively. As shown in the figure, as a result of adopting the midpoint of the chain cord, the line segment m becomes m1, m2,
Similarly, the line segment n is corrected to n1 and n2.

Here, the two line segments have been changed to four line segments. The newly adopted four line segments are checked to see if they interfere with each other. The number of vertices is increased by the same method (step 423).

If there is a twist in another place, the above-mentioned method is recursively repeated (step 424). When the number of line segments is increased most by performing the above-mentioned processing in the place where the twist exists, the newly generated line segment group corresponds to the chain code of the line segment section. Since this chain cord does not twist, there is no twist in the end. The twist removal processing described here can be sequentially performed when the chain code is approximated to a line segment.

After completely removing the twist, it is shown in FIG.
Pre-processing for single connection of outer and inner figures like
To do. Position when performing the process of connecting the outer and inner figures
The standard system is set as shown in FIG. First, as shown in Figure 43
, Y of the circumscribed rectangle of each inner figure pseudo from max to x-axis
A connecting line 450 is generated (step 431).

In the connection information table 412 of the internal figure that generated the pseudo connection line 450 shown in FIG. x value at max y A line segment number in max-a connection flag indicating which one of the internal figure and the external figure is connected-a graphic label of the connection destination-a line segment number of the connection destination-the x value of the connection destination is registered (step 432).

At the same time, in the line segment of the connected figure,
Register the number of connecting lines as the number of intersections. After generating pseudo connecting lines for all the internal figures, the template 414 of the connecting line table shown in FIG. 44 is created based on the counts registered in the line segments of the external figure and the internal figure, and is connected to each line segment. The head pointer of the line table 413 is registered (step 433).

This connecting line table is a table to be referred to when simply connecting an outer figure and an inner figure. The connected internal graphic label is registered in the connection line table while referring to the table information of the connection destination of each internal graphic (step 434).

After the inner graphic labels connected to the connecting line table are registered, referring to the connecting line table,
Connects outer and inner figures. For example, as shown in Figure 45,
The connection is started from the 0th vertex of the outer figure in the order of the vertex numbers, and if the end point of the pseudo connecting line exists in the line segment of the outer figure, it is registered via the pseudo connecting line. It is connected to the 0th vertex of the inner figure having the label number (see 460 in FIG. 45). The inner figure is also connected in the order of the vertex numbers, and if there is no end point of the pseudo connecting line generated from another inner figure in the line segment of the inner figure, the connection continues to the 0th vertex and the 0th vertex. When it reaches the apex of, it returns to the outer figure via the pseudo connecting line in the opposite direction to the previous one (see 461 in FIG. 45). If the inner figure has an end point of a pseudo connecting line generated from another inner figure, the end point is connected to the inner figure generating the pseudo connecting line through the pseudo connecting line. (See 462 in FIG. 45). 0 of the figure reached
The connection continues in the same way from the second vertex.

The outer figure and the inner figure are simply connected, as shown in FIG.
After the perforated figure as shown in FIG. 6 (a) is connected as shown in FIG. 6 (b), the vertex line of the contour line of the regenerated figure is used as shown in FIG. 6 (c). Considering the layers (z direction) of continuous faults, the generated closed figure can be placed on the top and bottom and the side can be added. As three-dimensional modeling, these plane data are generated for the number of continuous tomographic images.

The geometric information generated by the processor 41 is stored in the storage device 42, and the geometric information is drawn on the display device 44. Through a series of these processes, a three-dimensional structure faithful to the shape of the target object can be generated from the gradation data which is a continuous tomographic image of the target object in which a hole exists.

As described above, according to the fourth embodiment, when a plurality of figures different from itself exist inside the figure, the twist existing in the contour line of the figure is locally removed. Then, the outer figure and the inner figure are generated as one figure, and the vertex row of the figure can be obtained. As a result, it is possible to generate a patch for filling computer graphics by only considering the irregularities of the contour shape of the generated figure, and it is possible to perform the filling excluding a plurality of internal figures.

[0089]

According to the present invention, the hierarchical network information and the demand information in the target area are given, the network analysis for the rough network is executed, and the network analysis result in this rough network is used. The detailed network data corresponding to a small area is processed, and the network calculation for the detailed network is executed based on the processed detailed network data and the demand data for the detailed network. When a part of the area is specified, the detailed analysis results of the network can be calculated at high speed, and the local analysis of the network can be displayed quickly. become. This has a great effect on the display and presentation of the local analysis of the pipe network, for example.

Further, according to the present invention, when these display methods are registered for the graphic data and the attribute data and the display target area and the display target are selected for the graphic data and the attribute data, this selection is performed. Since the optimum display method for the display target is searched and the data display is performed for the displayed display target area, the display data can be effectively displayed by setting the appropriate viewpoint together with the graphic display such as a map of the target area. Can be displayed.

[Brief description of drawings]

FIG. 1 is a diagram showing a schematic configuration of a first embodiment of the present invention.

FIG. 2 is a diagram showing an example of hierarchical pipe network data according to the first embodiment.

FIG. 3 is a diagram showing an example of detailed node data of a pipe network according to the first embodiment.

FIG. 4 is a diagram showing an example of detailed arc network arc data in the first embodiment.

FIG. 5 is a diagram showing an example of the node data of the rough pipe network of the first embodiment.

FIG. 6 is a diagram showing an example of arc data of the rough pipe network of the first embodiment.

FIG. 7 is a diagram showing an example of demand data according to the first embodiment.

FIG. 8 is a diagram showing an example of designating a small area using the MMI / F of the first embodiment.

FIG. 9 is a diagram showing a schematic configuration of a second embodiment of the present invention.

FIG. 10 is a diagram showing graphic data registered in the database of the second embodiment.

FIG. 11 is a flowchart showing a data display of the second embodiment.

FIG. 12 is a diagram showing a knowledge base used in the second embodiment.

FIG. 13 is a diagram showing a relationship between a display target and a viewpoint distance according to the second embodiment.

FIG. 14 is a diagram for explaining a viewpoint candidate setting method according to the second embodiment.

FIG. 15 is a diagram showing an object for counting the number of pixels in the second embodiment.

FIG. 16 is a view for explaining movement of a viewpoint by a mouse according to the second embodiment.

FIG. 17 is a diagram showing a display example of simulation data according to the second embodiment.

FIG. 18 is a diagram showing a display example of figures and numerical data according to the second embodiment.

FIG. 19 is a diagram for explaining an example of simultaneously displaying display targets of different categories according to the second embodiment.

FIG. 20 is a diagram for explaining an example of simultaneously displaying display targets of different categories according to the second embodiment.

FIG. 21 is a diagram for explaining an example of simultaneously displaying display targets of different categories according to the second embodiment.

FIG. 22 is a diagram showing a schematic configuration of a third embodiment of the present invention.

FIG. 23 is a flowchart for explaining the operation of the third embodiment.

FIG. 24 is a diagram showing an example of a closed figure according to the third embodiment.

FIG. 25 is a diagram showing an example of generation of three-dimensional data according to the third embodiment.

FIG. 26 is a diagram showing an example of generating primitive data according to the third embodiment.

FIG. 27 is a diagram showing an example of generating primitive data according to the third embodiment.

FIG. 28 is a diagram showing an example of how to obtain a pseudo connecting line according to the third embodiment.

FIG. 29 is a flowchart showing a procedure for generating primitive data according to the third embodiment.

FIG. 30 is a view showing a cutting line in a slice of the third embodiment and a run cut by the cutting line.

FIG. 31 is a flowchart showing a procedure for obtaining a cutting point according to the third embodiment.

FIG. 32 is a diagram for explaining cutting points in the third embodiment.

FIG. 33 is a diagram showing an example of regenerating the primitive data according to the third embodiment.

FIG. 34 is a flowchart showing a graphic generation method according to the fourth embodiment of the present invention.

FIG. 35 is a diagram showing a schematic configuration of a fourth embodiment of the present invention.

FIG. 36 is a flowchart for explaining the operation of the fourth embodiment.

FIG. 37 is a diagram showing an inclusion relation list and a connection information table 412 of the fourth embodiment.

FIG. 38 is a diagram showing an example of a perforated graphic to be processed.

FIG. 39 is a flowchart showing the procedure of processing for removing twist in the fourth embodiment.

FIG. 40 is a diagram for explaining how to remove the twist generated by the line segment approximation of the fourth embodiment.

FIG. 41 is a flow chart showing a procedure of preprocessing for simply connecting outer and inner figures according to the fourth embodiment.

FIG. 42 is a diagram showing a coordinate system when performing preprocessing for single connection in the fourth example.

FIG. 43 is a view for explaining an operation example in preprocessing for single connection in the fourth example.

FIG. 44 is a diagram showing a connection line table and its template according to the fourth embodiment.

FIG. 45 is a diagram for explaining an example of single connection of outer and inner figures according to the fourth embodiment.

FIG. 46 is a diagram showing an example of three-dimensional modeling according to the fourth embodiment.

[Explanation of symbols]

1 ... Pipe network data, 2 ... Demand data, 11 ... Coarse pipe network data, 12 ... Detailed pipe network data, 3 ... MMI / F, 4 ... Demand data selector, 5 ... Pipe network data Selection unit, 6 ... Global result processing unit, 7 ... Global pipe network analysis unit, 8 ... Local pipe network analysis unit, 9 ... Display unit, 21, 31 ... CPU, 22
... DB, 23 ... KD, 24, 34 ... CRT, 25, 33
... MMI / F, 32 ... DISK, 241-243 ... Label, 244 ... Outer contour line, 245 ... Outer figure, 246 ... Inner contour line, 247 ... Inner figure, 248 ... Sibling figure, 261, ... Contour line, 271, 272 , 281, 282 ... Pseudo connecting line,
301 ... Cutting plane, 302 ... Starting point, 303 ... End point, 304
... Run, 305 ... Cutting point sequence, 321 ... Cutting point, 322 ...
Cutting line, 331 ... Cutting point sequence, 332 ... Closed figure, 40 ... Scanner, 41 ... Processor, 42 ... Storage device, 44 ... Display device, 411 ... Inclusion relation list, 412 ... Linkage information table, 413 ... Linkage table, 414 ... Template of connection line table, 441 ... Outer figures 441, 44
2, 443 ... Inside figure pseudo connecting line 450, L1, L2, L
3 ... Label, P1 to P13 ... Vertex.

 ─────────────────────────────────────────────────── ─── Continuation of front page (72) Inventor Osamu Hori No. 1 Komukai Toshiba-cho, Sachi-ku, Kawasaki-shi, Kanagawa Incorporated Toshiba Research and Development Center

Claims (3)

[Claims] 1. Means for preparing hierarchical pipeline network data and demand data having coarse pipeline network data and detailed pipeline network data for a target area, and analyzing the coarse pipeline network by the hierarchical pipeline network data and demand data. Means for executing, means for designating a sub-region of the network within the target area, detailed network data corresponding to the sub-region designated by this means, detailed network data of the hierarchical network data Means for selecting more, means for selecting demand data regarding a detailed network, means for processing the detailed network data selected corresponding to the small area by the analysis result for the rough network, A pipe network analyzing apparatus comprising: demand data relating to the detailed pipe network; and means for executing a pipe network calculation in the detailed pipe network based on the processed detailed pipe network data. 2. A means for storing graphic data and attribute data, a means for registering a display method for the graphic data and attribute data stored in this means, and a display target for the stored graphic data and attribute data. A data display comprising means for selecting an area and a display target, and means for displaying a data display by searching an optimum display method for the display target in the display target area selected by this means. apparatus. 3. A contour line of each figure is extracted from data of an outer figure composed of outer contour lines and data of at least one inner figure contained in the outer figure and composed of inner contour lines. And a second step of structuring the shape information of each of the outer figure and the inner figure and the inclusion relation between the figures based on each of the extracted contour lines. A pseudo connecting line for connecting the inner figure and the outer figure, or the inner figure and another inner figure included in the same outer figure that includes the inner figure based on the included shape information and the inclusion relationship. And a fourth step of generating one closed figure by connecting the contour lines of the figures by using the pseudo connecting line. .